
import mplfinance as mpf
import yfinance as yf
from wallstreet import get_daily_returns, get_ytd_growth_percentage, get_moving_averages, get_relative_strength
import pandas as pd
from datetime import datetime


datetime.now()

datetime.datetime(2022, 2, 14, 13, 55, 19, 968247)


pd.options.display.float_format = '{:.2f}'.format


symbol = 'ptlo'
week = '2022-03-18'
n = 10


# Parameters
symbol = "fl"
week = "2022-03-18"
n = 20


symbol = symbol.upper()
n = n * -1


get_daily_returns([symbol]).set_index('ticker').transpose()


get_ytd_growth_percentage([symbol]).set_index('ticker').transpose()


mav = get_moving_averages(symbol)
mav[-5:]

[*********************100%***********************]  1 of 1 completed


mas = [mpf.make_addplot(mav[n:]['SMA8'],color='green'),
       mpf.make_addplot(mav[n:]['SMA21'], color='blue'),
       mpf.make_addplot(mav[n:]['SMA30'], color='orange'),
       ]
if ('SMA200' in mav.keys()):
       mas.append(mpf.make_addplot(mav[n:]['SMA200'], color='red', linestyle='dashed'))

mpf.plot(mav[n:], type='candle',style='charles',title='\n{}'.format(symbol),volume=True,addplot=mas,figscale=1.1,figratio=(3,2))


e = yf.Ticker(symbol)
hist = e.history(period='60d', interval='1d')
# Valid intervals: [1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo]

# expiration weeks
exp_weeks = pd.DataFrame(e.options, columns=['weeks'])
# exp_weeks

hlines=None

if week in exp_weeks.weeks.values:
  opt = e.option_chain(week)
  c_asset = pd.DataFrame(opt.calls, columns=['strike', 'volume','openInterest', 'impliedVolatility'])
  call_strike = c_asset[c_asset.openInterest == c_asset.openInterest.max()].set_index('strike').index[0]
  p_asset = pd.DataFrame(opt.puts, columns=['strike', 'volume','openInterest', 'impliedVolatility'])
  put_strike = p_asset[p_asset.openInterest == p_asset.openInterest.max()].set_index('strike').index[0]
  hlines = dict(hlines=(put_strike, call_strike), colors=('r','g','b','b'), linewidths=(1,1),linestyle='dashed')

# Settings
kwargs = dict(figscale=1.1,figratio=(8,4),
         volume=True,volume_panel=2,panel_ratios=(7,2,2) , mav=(8,21,30))

exp12 = hist['Close'].ewm(span=12, adjust=False).mean()
exp26 = hist['Close'].ewm(span=26, adjust=False).mean()
macd = exp12 - exp26
signal    = macd.ewm(span=9, adjust=False).mean()
histogram = macd - signal

currentPrice = hist[-1:].set_index('Close').index[0]

apds = [#mpf.make_addplot(exp12,color='lime'),
        #mpf.make_addplot(exp26,color='c'),
        mpf.make_addplot(histogram,type='bar',width=0.4,panel=1,
                         color='blue',alpha=1,secondary_y=False),
        mpf.make_addplot(macd,panel=1,color='green',secondary_y=True),
        mpf.make_addplot(signal,panel=1,color='purple',secondary_y=True),
       ]


# mpf.plot(hist,type='candle',style='yahoo',addplot=apds,**kwargs,hlines=hlines)


if hlines:
  title = '\n{} {:.2f} \nOptions Open Interest Walls\n Exp Date: {} Call: {:.2f} Put: {:.2f}'.format(symbol, currentPrice, week, call_strike, put_strike)
  mpf.plot(hist,type='candle',style='default',addplot=apds,**kwargs,hlines=hlines,title=title)
else:
  title = '\n{} {:.2f} \n'.format(symbol, currentPrice)
  mpf.plot(hist,type='candle',style='default',addplot=apds,**kwargs,title=title)

ticker	FL
name	Foot Locker, Inc.
previous_close	43.85
current_price	43.32
percent change	-1.21
today_volume	0.76
previous_volume	1.23

ticker	FL
name	Foot Locker, Inc.
growth	-0.06

	Open	High	Low	Close	Adj Close	Volume	SMA8	SMA21	SMA30	SMA200	RSI
Date
2022-02-08	43.39	44.94	43.34	44.27	44.27	1173700	43.60	43.71	43.53	52.78	50.15
2022-02-09	44.65	45.01	44.35	44.89	44.89	932800	43.65	43.85	43.62	52.71	52.18
2022-02-10	44.47	45.59	44.08	44.40	44.40	1007300	43.62	43.94	43.64	52.64	50.47
2022-02-11	44.39	44.75	43.57	43.85	43.85	1232000	43.54	43.97	43.64	52.56	48.59
2022-02-14	43.91	44.50	42.98	43.30	43.30	761100	43.55	43.98	43.63	52.48	46.77

TheDailyCalls.com Notebook¶

Date¶

Performance¶

Daily Returns¶

Year to date returns¶

Moving Averages¶

Graph¶